In real time tracking system

the size of tracking window should be updated when the scale of the moving object is being varied

which is corresponding to the scale change of mean shift. In order to solve the problem

this paper proposed a method to catch the adaptive scale change. Firstly

the corner points are detected in the tracking window. Secondly

the detected points are matched with the preceding frame

and the affine model is constructed based on the matching results. Thirdly

least square method is taken to induce the scale coefficients. Lastly

the obtained scale is applied to the mean shift tracking framework. Experimental results show the improved algorithm could track objects precisely when scale of the object changes progressively

as well as is robust and operated real time.